| 粗糙集的RBF表示与非监督模式分类 |
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| 引用本文： | 魏敏洁,刘健勤.粗糙集的RBF表示与非监督模式分类[J].湖南科技大学学报(自然科学版),1998(2). |
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| 作者姓名： | 魏敏洁 刘健勤 |
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| 作者单位： | 中南工业大学信息工程学院 |
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| 基金项目： | 国家教委图像信息处理与智能控制开放实验室基金,湖南省自然科学基金 |
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| 摘 要： | 提出了一种粗糙集的ＲＢＦ网络表示形式，在集值测度意义下，将粗糙集的语义表达进行了有效的描述，并构造了其自适应自组织的遗传学习机制．其创新性主要表现在：（１）通过ＲＢＦ网络有效地构造了粗糙集在模式分类中的自适应表示形式；（２）在遗传算法中引入了元进化自调整机制；（３）以粗糙集意义下的非线性映射方式提高了模式分类的计算效率．图３，表１，参４．
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| 关 键 词： | 粗糙集 人工生命 遗传算法 模式分类 |
RBF REPRESENTATION AND UNSUPERVISED PATTERN CLASSIFICATION BASED ON ROUGH SETS |
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| Wei Minjie,Liu Jianqin.RBF REPRESENTATION AND UNSUPERVISED PATTERN CLASSIFICATION BASED ON ROUGH SETS[J].Journal of Hunan University of Science & Technology(Natural Science Editon),1998(2). |
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| Authors: | Wei Minjie Liu Jianqin |
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| Abstract: | In this paper, a kind of RBF network representation form based on rough sets is proposed.Under the meaning of set-valued measure,the semantic expression of rough sets is efficiently described and a genetic learning mechanism with the characteristics of self-adaptation and self-organization is constructed.Compared with existing technics,the originalities of the research work proposed in the paper are mainly in following three aspects:(1)An adapative representation form in pattern classification using rough sets is constructed through RBF network.(2)A self-adjustable mechanism is introduced to the genetic algorithm.(3)The computational efficency has been greatly improved through non-linear mapping under rough sets.3figs.,1tab,4refs. |
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| Keywords: | rough sets man-made life genetic algorithm pattern classification |
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